Papers by Xingyu Tan

3 papers
Building LLMs Like LEGO: Two-dimensional Architecture Reassembly of Large Language Models (2026.acl-long)

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Challenge: Existing approaches to LLM reuse treat LLMs as monolithic artifacts.
Approach: They propose to recompose pretrained large language models as modular building blocks . they propose a chromosome-based architectural encoding and evolutionary optimization .
Outcome: The proposed model can be recomposed as modular building blocks without training data.
End-to-End Open-Domain Question Answering with BERTserini (N19-4)

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Challenge: a new open-domain question answering system integrates best practices from IR with a BERT-based reader to identify answers from a large corpus of Wikipedia articles.
Approach: They propose an end-to-end question answering system that integrates BERT with an IR reader.
Outcome: The proposed system improves on a standard benchmark test collection.
HydraRAG: Structured Cross-Source Enhanced Large Language Model Reasoning (2025.emnlp-main)

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Challenge: Current RAG system retrieves evidence from knowledge graphs and text documents but has limitations in multi-hop reasoning, multi-entity questions, and source verification.
Approach: They propose a training-free framework that unifies graph topology, document semantics, and source reliability to support deep, faithful reasoning in large language models.
Outcome: The proposed framework outperforms the current hybrid model-based model-driven system by 20.3% and 30.1% on seven benchmark datasets.

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